References of "Glaab, Enrico 50001863"
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See detailTranscriptome profiling data reveals Ubiquitin-Specific Peptidase 9 knockdown effects
Glaab, Enrico UL; Antony, Paul UL; Köglsberger, Sandra et al

in Data in Brief (in press)

Ubiquitin specific peptidase 9 (USP9) is a deubiquitinase encoded by a sex-linked gene with a Y-chromosomal form (USP9Y) and an X-chromosomal form (USP9X) that escapes X-inactivation. Since USP9 is a key ... [more ▼]

Ubiquitin specific peptidase 9 (USP9) is a deubiquitinase encoded by a sex-linked gene with a Y-chromosomal form (USP9Y) and an X-chromosomal form (USP9X) that escapes X-inactivation. Since USP9 is a key regulatory gene with sex-linked expression in the human brain, the gene may be of interest for researchers studying molecular gender differences and ubiquitin signaling in the brain. To assess the downstream effects of knocking down USP9X and USP9Y on a transcriptome-wide scale, we have conducted microarray profiling experiments using the human DU145 prostate cancer cell culture model, after confirming the robust expression of both USP9X and USP9Y in this model. By designing shRNA constructs for the specific knockdown of USP9X and the joint knockdown of USP9X and USP9Y, we have compared gene expression changes in both knockdowns to control conditions to infer potential shared and X- or Y-form specific alterations. Here, we provide details of the corresponding microarray profiling data, which has been deposited in the Gene Expression Omnibus database (GEO series accession number GSE79376). A biological interpretation of the data in the context of a potential involvement of USP9 in Alzheimer’s disease has previously been presented in Köglsberger et al. (2016). To facilitate the re-use and re-analysis of the data for other applications, e.g. the study of ubiquitin signaling and protein turnover control, and the regulation of molecular gender differences in the human brain and brain-related disorders, we provide a more in-depth discussion of the data properties, specifications and possible use cases. [less ▲]

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See detailIntegrative analysis of blood metabolomics and PET brain neuroimaging data for Parkinson's disease
Glaab, Enrico UL; Trezzi, Jean-Pierre UL; Greuel, Andrea et al

in Neurobiology of Disease (2019), 124(1), 555-562

The diagnosis of Parkinson's disease (PD) often remains a clinical challenge. Molecular neuroimaging can facilitate the diagnostic process. The diagnostic potential of metabolomic signatures has recently ... [more ▼]

The diagnosis of Parkinson's disease (PD) often remains a clinical challenge. Molecular neuroimaging can facilitate the diagnostic process. The diagnostic potential of metabolomic signatures has recently been recognized. Methods: We investigated whether the joint data analysis of blood metabolomics and PET imaging by machine learning provides enhanced diagnostic discrimination and gives further pathophysiological insights. Blood plasma samples were collected from 60 PD patients and 15 age- and gender-matched healthy controls. We determined metabolomic profiles by gas chromatography coupled to mass spectrometry (GC-MS). In the same cohort and at the same time we performed FDOPA PET in 44 patients and 14 controls and FDG PET in 51 patients and 16 controls. 18 PD patients were available for a follow-up exam after one year. Both data sets were analysed by two machine learning approaches, applying either linear support vector machines or random forests within a leave-one-out cross-validation and computing receiver operating characteristic (ROC) curves. Results: In the metabolomics data, the baseline comparison between cases and controls as well as the followup assessment of patients pointed to metabolite changes associated with oxidative stress and inflammation. For the FDOPA and FDG PET data, the diagnostic predictive performance (DPP) in the ROC analyses was highest when combining imaging features with metabolomics data (ROC AUC for best FDOPA + metabolomics model: 0.98; AUC for best FDG + metabolomics model: 0.91). DPP was lower when using only PET attributes or only metabolomics signatures. Conclusion: Integrating blood metabolomics data combined with PET data considerably enhances the diagnostic discrimination power. Metabolomic signatures also indicate interesting disease-inherent changes in cellular processes, including oxidative stress response and inflammation. [less ▲]

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See detailWeb-based QTL linkage analysis and bulk segregant analysis of yeast sequencing data
Zhang, Zhi; Jung, Paul; Groues, Valentin UL et al

in GigaScience (2019), 8(6), 060

Quantitative Trait Loci (QTL) mapping using bulk segregants is an effective approach for identifying genetic variants associated with phenotypes of interest in model organisms. By exploiting next ... [more ▼]

Quantitative Trait Loci (QTL) mapping using bulk segregants is an effective approach for identifying genetic variants associated with phenotypes of interest in model organisms. By exploiting next-generation sequencing technology, the QTL mapping accuracy can be improved significantly, providing a valuable means to annotate new genetic variants. However, setting up a comprehensive analysis framework for this purpose is a time-consuming and error prone task, posing many challenges for scientists with limited experience in this domain. Findings: Here, we present BSA4Yeast, a comprehensive web-application for QTL mapping via bulk segregant analysis of yeast sequencing data. The software provides an automated and efficiency-optimized data processing, up-to-date functional annotations, and an interactive web-interface to explore identified QTLs. Conclusion: BSA4Yeast enables researchers to identify plausible candidate genes in QTL regions efficiently in order to validate their genetic variations experimentally as causative for a phenotype of interest. BSA4Yeast is freely available at https://bsa4yeast.lcsb.uni.lu. [less ▲]

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See detail3D Cultures of Parkinson's Disease‐Specific Dopaminergic Neurons for High Content Phenotyping and Drug Testing
Bolognin, Silvia UL; Fossépré, Marie; Qing, Xiaobing et al

in Advanced Science (2018)

Parkinson's disease (PD)‐specific neurons, grown in standard 2D cultures, typically only display weak endophenotypes. The cultivation of PD patient‐specific neurons, derived from induced pluripotent stem ... [more ▼]

Parkinson's disease (PD)‐specific neurons, grown in standard 2D cultures, typically only display weak endophenotypes. The cultivation of PD patient‐specific neurons, derived from induced pluripotent stem cells carrying the LRRK2‐G2019S mutation, is optimized in 3D microfluidics. The automated image analysis algorithms are implemented to enable pharmacophenomics in disease‐relevant conditions. In contrast to 2D cultures, this 3D approach reveals robust endophenotypes. High‐content imaging data show decreased dopaminergic differentiation and branching complexity, altered mitochondrial morphology, and increased cell death in LRRK2‐G2019S neurons compared to isogenic lines without using stressor agents. Treatment with the LRRK2 inhibitor 2 (Inh2) rescues LRRK2‐G2019S‐dependent dopaminergic phenotypes. Strikingly, a holistic analysis of all studied features shows that the genetic background of the PD patients, and not the LRRK2‐G2019S mutation, constitutes the strongest contribution to the phenotypes. These data support the use of advanced in vitro models for future patient stratification and personalized drug development. [less ▲]

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See detailCombining PET imaging and blood metabolomics data to improve machine learning models for Parkinson’s disease diagnosis
Glaab, Enrico UL; Trezzi, Jean-Pierre UL; Greuel et al

Poster (2018, October 08)

Objective: To investigate whether the integration of PET imaging and metabolomics data can provide improved machine learning models for PD diagnosis. Background: The reliable diagnosis of PD can remain ... [more ▼]

Objective: To investigate whether the integration of PET imaging and metabolomics data can provide improved machine learning models for PD diagnosis. Background: The reliable diagnosis of PD can remain challenging, even at the motor stage. PET imaging can be used to confirm the clinical diagnosis. However, limitations in the robustness of predictive features extracted from the data and the costs associated with PET imaging restrict its application. Using blood metabolomics data as an additional information source may provide improved combined diagnostic models and/or an initial filter to decide on whether to apply PET imaging. Methods: Metabolomics profiling of blood plasma samples using gas chromatography coupled to mass spectrometry (GC­MS) was conducted in 60 IPD patients and 15 healthy controls. After pre-processing, these data were compared to neuroimaging data for subsets of the same individuals using FDOPA PET (44 patients and 14 controls) and FDG PET (51 patients and 15 controls). Machine learning models using linear support vector machines were trained on 50% of the data and evaluated on a 50% hold­out test set using Receiver Operating Characteristic (ROC) curves. Next, standardized FDOPA and FDG PET intensity measurements were combined with those from the metabolomics data to build and evaluate sample classification models in the same manner as for the individual datasets. Results: Both for the FDOPA and FDG PET data, the predictive performance given by the area under the ROC curve (AUC) was highest when combining imaging features with those from the metabolomics data (AUC for FDOPA + metabolomics: 0.98; AUC for FDG + metabolomics: 0.91). The performance was generally lower when using only the respective PET attributes (FDOPA: 0.94, FDG: 0.8) or only the metabolomics data (AUC: 0.66). [less ▲]

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See detailIntegrative analysis of mitochondrial changes in Parkinson’s disease
Glaab, Enrico UL

Presentation (2018, July 16)

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See detailA rare loss-of function variant of ADAM17 is associated with late-onset familial Alzheimer disease
Hartl, Daniela; May, Patrick UL; Gu, Wei UL et al

in Molecular Psychiatry (2018)

Common variants of about 20 genes contributing to AD risk have so far been identified through genome-wide association studies (GWAS). However, there is still a large proportion of heritability that might ... [more ▼]

Common variants of about 20 genes contributing to AD risk have so far been identified through genome-wide association studies (GWAS). However, there is still a large proportion of heritability that might be explained by rare but functionally important variants. One of the so far identified genes with rare AD causing variants is ADAM10. Using whole-genome sequencing we now identified a single rare nonsynonymous variant (SNV) rs142946965 [p.R215I] in ADAM17 co-segregating with an autosomal-dominant pattern of late-onset AD in one family. Subsequent genotyping and analysis of available whole-exome sequencing data of additional case/control samples from Germany, the UK and the USA identified five variant carriers among AD patients only. The mutation inhibits pro-protein cleavage and the formation of the active enzyme, thus leading to loss-of-function of ADAM17 α-secretase. Further, we identified a strong negative correlation between ADAM17 and APP gene expression in human brain and present in vitro evidence that ADAM17 negatively controls the expression of APP. As a consequence, p.R215I mutation of ADAM17 leads to elevated Aß formation in vitro. Together our data supports a causative association of the identified ADAM17 variant in the pathogenesis of AD. [less ▲]

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See detailComputational systems biology approaches for Parkinson's disease
Glaab, Enrico UL

in Cell and Tissue Research (2018), 373(1), 91109

Parkinson’s disease (PD) is a prime example of a complex and heterogeneous disorder, characterized by multifaceted and varied motor- and non-motor symptoms and different possible interplays of genetic and ... [more ▼]

Parkinson’s disease (PD) is a prime example of a complex and heterogeneous disorder, characterized by multifaceted and varied motor- and non-motor symptoms and different possible interplays of genetic and environmental risk factors. While investigations of individual PD-causing mutations and risk factors in isolation are providing important insights to improve our understanding of the molecular mechanisms behind PD, there is a growing consensus that a more complete understanding of these mechanisms will require an integrative modeling of multifactorial disease-associated perturbations in molecular networks. Identifying and interpreting the combinatorial effects of multiple PD-associated molecular changes may pave the way towards an earlier and reliable diagnosis and more effective therapeutic interventions. This review provides an overview of computational systems biology approaches developed in recent years to study multifactorial molecular alterations in complex disorders, with a focus on PD research applications. Strengths and weaknesses of different cellular pathway and network analyses, and multivariate machine learning techniques for investigating PD-related omics data are discussed, and strategies proposed to exploit the synergies of multiple biological knowledge and data sources. A final outlook provides an overview of specific challenges and possible next steps for translating systems biology findings in PD to new omics-based diagnostic tools and targeted, drug-based therapeutic approaches. [less ▲]

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See detailCombined analysis of neuroimaging and metabolomics data for Parkinson’s disease
Glaab, Enrico UL

Presentation (2018, June 28)

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See detailA structure-activity relationship linking non-planar PCBs to functional deficits of neural crest cells: new roles for connexins
Nyffeler, Johanna; Chovancova, Petra; Dolde, Xenia et al

in Archives of Toxicology (2018), 92(3), 12251247

Migration of neural crest cells (NCC) is a fundamental developmental process, and test methods to identify interfering toxicants have been developed. By examining cell function endpoints, as in the ... [more ▼]

Migration of neural crest cells (NCC) is a fundamental developmental process, and test methods to identify interfering toxicants have been developed. By examining cell function endpoints, as in the ‘migration-inhibition of NCC (cMINC)’ assay, a large number of toxicity mechanisms and protein targets can be covered. However, the key events that lead to the adverse effects of a given chemical or group of related compounds are hard to elucidate. To address this issue, we explored here, whether the establishment of two overlapping structure–activity relationships (SAR)—linking chemical structure on the one hand to a phenotypic test outcome, and on the other hand to a mechanistic endpoint—was useful as strategy to identify relevant toxicity mechanisms. For this purpose, we chose polychlorinated biphenyls (PCB) as a large group of related, but still toxicologically and physicochemically diverse structures. We obtained concentration-dependent data for 26 PCBs in the cMINC assay. Moreover, the test chemicals were evaluated by a new high-content imaging method for their effect on cellular re-distribution of connexin43 and for their capacity to inhibit gap junctions. Non-planar PCBs inhibited NCC migration. The potency (1–10 μM) correlated with the number of ortho-chlorine substituents; non-ortho-chloro (planar) PCBs were non-toxic. The toxicity to NCC partially correlated with gap junction inhibition, while it fully correlated (p < 0.0004) with connexin43 cellular re-distribution. Thus, our double-SAR strategy revealed a mechanistic step tightly linked to NCC toxicity of PCBs. Connexin43 patterns in NCC may be explored as a new endpoint relevant to developmental toxicity screening. [less ▲]

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See detailFDG-PET and metabolomics in PD-associated GBA variants
Greuel, Andrea; Trezzi, Jean-Pierre; Glaab, Enrico UL et al

in Movement Disorders (2018), 33(2), 599

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See detailGender-specific expression of ubiquitin-specific peptidase 9 modulates tau expression and phosphorylation: possible implications for tauopathies
Köglsberger, Sandra UL; Cordero Maldonado, Maria Lorena UL; Antony, Paul UL et al

in Molecular Neurobiology (2017), 54(10), 79797993

Public transcriptomics studies have shown that several genes display pronounced gender differences in their expression in the human brain, which may influence the manifestations and risk for neuronal ... [more ▼]

Public transcriptomics studies have shown that several genes display pronounced gender differences in their expression in the human brain, which may influence the manifestations and risk for neuronal disorders. Here we apply a transcriptome-wide analysis to discover genes with gender-specific expression and significant alterations in public post mortem brain tissue from Alzheimer’s disease (AD) patients compared to controls. We identify the sex-linked ubiquitin specific peptidase 9 (USP9) as an outstanding candidate gene with highly significant expression differences between the genders and male-specific under-expression in AD. Since previous studies have shown that USP9 can modulate the phosphorylation of the AD-associated protein MAPT, we investigate functional associations between USP9 and MAPT in further detail. After observing a high positive correlation between the expression of USP9 and MAPT in the public transcriptomics data, we show that USP9 knockdown results in significantly decreased MAPT expression in a DU145 cell culture model and a concentration-dependent decrease for the MAPT orthologs mapta and maptb in a zebrafish model. From the analysis of microarray and qRT-PCR experiments for the knockdown in DU145 cells and prior knowledge from the literature, we derive a data-congruent model for a USP9-dependent regulatory mechanism modulating MAPT expression via BACH1 and SMAD4. Overall, the analyses suggest USP9 may contribute to molecular gender differences observed in tauopathies and provide a new target for intervention strategies to modulate MAPT expression. [less ▲]

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See detailAbsence of regulator of G-protein signaling 4 does not protect against dopamine neuron dysfunction and injury in the mouse 6-hydroxydopamine lesion model of Parkinson's disease
Ashrafi, Amer UL; Garcia, Pierre UL; Kollmus, Heike et al

in Neurobiology of Aging (2017), 58

Regulator of G-Protein Signaling 4 (RGS4), a member of the RGS family of proteins that inactivate G-proteins, has gained interest as a potential drug target for neurological disorders, such as epilepsy ... [more ▼]

Regulator of G-Protein Signaling 4 (RGS4), a member of the RGS family of proteins that inactivate G-proteins, has gained interest as a potential drug target for neurological disorders, such as epilepsy and Parkinson’s disease (PD). In the case of PD, the main current option for alleviating motor symptoms are dopamine replacement therapies, which have limitations because of side effects, and reduced effectiveness over the long term. Research on new non-dopaminergic PD drug targets has indicated that inhibition of RGS4 could be an effective adjuvant treatment option. The effectiveness of RGS4 inhibition for an array of PD-linked functional and structural neuroprotection endpoints has not yet been demonstrated. Here, we use the 6-Hydroxydopamine (6-OHDA) lesioning model of the nigrostriatal pathway in mice to address this question. We observe, using a battery of behavioral and pathological measures, that mice deficient for RGS4 are not protected from 6-OHDA induced injury, and show enhanced susceptibility in some measures of motor function. Our results suggest that inhibition of RGS4 as a non-dopaminergic target for PD should be approached with caution. [less ▲]

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See detailMetformin reverses TRAP1 mutation-associated alterations in mitochondrial function in Parkinson's disease
Fitzgerald, Julia C.; Zimprich, Alexander; Carvajal-Berrio, Daniel A. et al

in Brain : A Journal of Neurology (2017), 140(9), 2444-2459

The mitochondrial proteins TRAP1 and HtrA2 have previously been shown to be phosphorylated in the presence of the Parkinson’s disease kinase PINK1 but the downstream signaling is unclear. HtrA2 and PINK1 ... [more ▼]

The mitochondrial proteins TRAP1 and HtrA2 have previously been shown to be phosphorylated in the presence of the Parkinson’s disease kinase PINK1 but the downstream signaling is unclear. HtrA2 and PINK1 loss of function causes parkinsonism in humans and animals. Here, we identified TRAP1 as an interactor of HtrA2 using an unbiased mass spectrometry approach. In our human cell models, TRAP1 overexpression is protective, rescuing HtrA2 and PINK1-associated mitochondrial dysfunction and suggesting that TRAP1 acts downstream of HtrA2 and PINK1. HtrA2 regulates TRAP1 protein levels, but TRAP1 is not a direct target of HtrA2 protease activity. Following genetic screening of Parkinson’s disease patients and healthy controls, we also report the first TRAP1 mutation leading to complete loss of functional protein in a patient with late onset Parkinson’s disease. Analysis of fibroblasts derived from the patient reveal that oxygen consumption, ATP output and reactive oxygen species are increased compared to healthy individuals. This is coupled with an increased pool of free NADH, increased mitochondrial biogenesis, triggering of the mitochondrial unfolded protein response, loss of mitochondrial membrane potential and sensitivity to mitochondrial removal and apoptosis. These data highlight the role of TRAP1 in the regulation of energy metabolism and mitochondrial quality control. Interestingly, the diabetes drug metformin reverses mutation-associated alterations on energy metabolism, mitochondrial biogenesis and restores mitochondrial membrane potential. In summary, our data show that TRAP1 acts downstream of PINK1 and HtrA2 for mitochondrial fine tuning, whereas TRAP1 loss of function leads to reduced control of energy metabolism, ultimately impacting mitochondrial membrane potential. These findings offer new insight into mitochondrial pathologies in Parkinson’s disease and provide new prospects for targeted therapies. [less ▲]

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See detailNeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases
Blauwendraat, Cornelis; Faghri, Faraz; Pihlstrom, Lasse et al

in Neurobiology of Aging (2017)

Genetics has proven to be a powerful approach in neurodegenerative diseases research, resulting in the identification of numerous causal and risk variants. Previously, we introduced the NeuroX Illumina ... [more ▼]

Genetics has proven to be a powerful approach in neurodegenerative diseases research, resulting in the identification of numerous causal and risk variants. Previously, we introduced the NeuroX Illumina genotyping array, a fast and efficient genotyping platform designed for the investigation of genetic variation in neurodegenerative diseases. Here, we present its updated version, named NeuroChip. The NeuroChip is a low cost, custom-designed array containing a tagging variant backbone of about 306,670 variants complemented with a manually curated custom content comprised of 179,467 variants implicated in diverse neurological diseases, including Alzheimer’s disease, Parkinson’s disease, Lewy body dementia, amyotrophic lateral sclerosis, frontotemporal dementia, progressive supranuclear palsy, corticobasal degeneration and multiple system atrophy. The tagging backbone was chosen because of the low cost and good genome-wide resolution; the custom content can be combined with other backbones, like population or drug development arrays. Using the NeuroChip, we can accurately identify rare variants and impute over 5.3 million common SNPs from the latest release of the Haplotype Reference Consortium. In summary, we describe the design and usage of the NeuroChip array, and show its capability for detecting rare pathogenic variants in numerous neurodegenerative diseases. The NeuroChip has a more comprehensive and improved content, which makes it a reliable, high-throughput, cost-effective screening tool for genetic research and molecular diagnostics in neurodegenerative diseases. [less ▲]

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See detailBiomedical Data Science at LCSB
Glaab, Enrico UL

Presentation (2017)

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See detailIDENTIFICATION OF A RARE GENE VARIANT THAT IS ASSOCIATED WITH FAMILIAL ALZHEIMER DISEASE AND REGULATES APP EXPRESSION
Hartl, Daniela; May, Patrick UL; Gu, Wei UL et al

in Alzheimer's & Dementia : The Journal of the Alzheimer's Association (2017), 13(7, Supplement), 648

Background Genetic mutations leading to familial forms of Alzheimer disease (AD) have so far been reported for a few genes including APP, PSEN1 and PSEN2, UNC5C, PLD3, ABCA7, TTC3, and possibly ADAM10 ... [more ▼]

Background Genetic mutations leading to familial forms of Alzheimer disease (AD) have so far been reported for a few genes including APP, PSEN1 and PSEN2, UNC5C, PLD3, ABCA7, TTC3, and possibly ADAM10. With the advent of whole exome and whole genome sequencing approaches new genes and mutations are likely to be identified. Methods We analyzed the genetic cause of AD in a large multiplex family with an autosomal-dominant pattern of inheritance with LOAD. The family lacked pathogenic mutations of known AD genes. We performed whole-genome sequencing (WGS) in six family members (two affected and four unaffected) and prioritized rare, potential damaging, variants that segregated with disease. Variants were further characterized by subsequent molecular analyzes in human brain and cell culture models. Results We identified a single rare nonsynonymous variant co-segregating with AD. The mutation inhibits pro-protein cleavage and the formation of the active enzyme, thus leading to a loss-of-function of the gene. We further found a strong negative correlation between the identified gene and APP gene expression in human brain and in cells over-expressing the gene. The negative regulation of APP expression was only observed for the wt gene, but not for mutated forms, thus causing beside the loss of enzyme function a decoupling of both APPexpression and subsequent beta-amyloid formation. The identity of the gene will be presented on the conference. Conclusions This novel pathway strongly supports a causative association of the identified gene with the pathogenesis of AD. [less ▲]

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